Abstract
Abstract A full range of sampling strategies is required to support the analysis of remotely sensed data and other geographically referenced digital data in image format. Random samples generated from coordinate lists and compiled in attribute tables are critical in the selection of classifier algorithms and mapping variables, training and test area field site selection, and determination of classification accuracy. This paper introduces a number of programs which were written to implement a comprehensive sampling package in two different operating environments. Image data are extracted as samples that can be stratified by class or other variable, and can be sorted into training and test pixel tables. An illustration of the programs in classification accuracy assessment of a SPOT satellite image for classification of vegetation patterns in subarctic Canada is used to highlight the functionality of the system.
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